AI Is Transforming Healthcare
AI is increasingly transforming healthcare. The rapid advancement in artificial intelligence technology is driving significant changes across many industries including medicine. Artificial intelligence (AI) has the potential to transform how healthcare is delivered.
AI promises to be an important enabler for better patient care and health outcomes. There have been several examples where AI applications have demonstrated superior performance compared to human experts at specific tasks such as diagnosing medical conditions or performing surgical procedures.
This shift from expert systems that mimic human decision-making processes towards machine learning algorithms that can make decisions based on patterns observed by data sets presents new challenges for doctors, nurses, and other caregivers who may need to adapt their practices accordingly.
In this article we discuss some of the ways in which Artificial Intelligence is being used today in healthcare delivery, and look ahead to its future role in improving quality and efficiency of healthcare services. This leads to several benefits for Healthcare Companies.
Artificial Intelligence in Healthcare
AI-led improvements in healthcare can be grouped under six key areas:
- Decision making & Triage
- Diagnostics
- Clinical Decisions
- Healthcare Delivery
- Administration & Operations
- Innovation
These improvements result in, amongst others, cost reductions, surge in efficiency, better healthcare outcome and so on. The improvements can be monumental, in many cases.
Cost Reduction & Efficiency Improvements
In addition to providing better care, Artificial Intelligence could also help reduce costs associated with delivering healthcare. For example, there are claims that AI can significantly automate administrative work related to billing and coding using computer vision technology. Another startup uses AI to assist radiologists during routine exams. They claim that their system reduces errors by up to 40%-50%, allowing them to spend more time looking at interesting parts of the images rather than spending all day reading through reports.
Such developments should lead to improved efficiencies throughout the process of delivering healthcare. As a result, healthcare providers can focus on what matters most: treating patients effectively.
Improved Clinical Decision Making
Healthcare professionals are already using Artificial Intelligence tools to improve clinical decision making. These include techniques such as deep learning models that use neural networks to classify disease severity and predict treatment responses. In radiology, for example, AI could offer improved diagnosis and treatment with fewer errors.
Other approaches involve integrating natural language processing into electronic medical records to allow physicians to ask questions about symptoms and receive answers back in plain English.
Such developments should lead to improved efficiencies throughout the process of delivering healthcare. As a result, healthcare providers can focus on what matters most: treating patients effectively.
Expanding Use Cases
Artificial Intelligence is not limited to just assisting doctors in diagnosis and treatment; it’s being applied to expanded use cases as well.
Adverse Drug Reactions (ADRs)
One application involves helping to prevent adverse drug reactions. The FDA estimates that 10% – 20% of hospital admissions are caused by medication side effects.
For example (Source: NCBI, NIH), for hospitalizations:
- In the elderly: 1 in 30 hospital admissions are due to an ADE (Adverse Drug Effect)
- ADEs total one-third of total hospital adverse events
- The average hospitalized patient experiences at least one medication error each day
In fact, a recent Harvard study shows that “…adverse events from medication use and prescription drugs accounted for more than 110,000 deaths in the United States in 2019”. This the impact Adverse Drug Reactions and Adverse Drug Effects can have on healthcare efficiency and costs.
237+ million medication errors made every year in England, according to BMJ.
AI presents unique opportunities as well. For example, AI systems already developed can detect falls among elderly patients in nursing homes. By detecting when patients fall down, the system triggers alarms and summons assistance. Smartwatches and smart-bands are commercializing this previously unavailable opportunity.
Artificial Intelligence algorithms can be developed to identify high risk medications to prevent such ADEs and reduce costs and improve efficiency. There are many other ways in which Artificial Intelligence is being used to support the delivery of healthcare.
Healthcare Delivery
There are many other ways in which Artificial Intelligence is being used to support the delivery of healthcare. Many healthcare companies are using/developing chatbots designed to interact with people over email or social media platforms. Others provide virtual assistants that can answer questions or schedule appointments. Still others help patients find information online or monitor their health status remotely. I expect to see turbo-charged development in this area in coming years.
Many challenges that must be overcome before AI can become widely used in health care: privacy concerns; legal issues; cost-effectiveness; interoperability between different systems, and many others.
It’s important to remember, however, that while Artificial Intelligence can be very useful in certain circumstances, it cannot replace human judgment. Artificial intelligence algorithms can only perform tasks that have been programmed into them. A doctor with expertise in diagnosing medical conditions or performing surgical procedures is still needed to make decisions beyond those that can be automated.
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